We examine the Stein-rule shrinkage estimator for possible improvements in estimation and forecasting when there are many predictors in a linear time series model. We consider the Stein-rule estimator of Hill and Judge (1987) that shrinks the unrestricted unbiased ordinary least squares (OLS)...

This volume of Advances in Econometrics is devoted to dynamic stochastic general equilibrium (DSGE) models, which have gained popularity in both academic and policy circles as a theoretically and methodologically coherent way of analyzing a variety of issues in empirical macroeconomics. The...

Apart from the well-known, high persistence of daily financial volatility data, there is also a short correlation structure that reverts to the mean in less than a month. We find this short correlation time scale in six different daily financial time series and use it to improve the short-term...

In GARCH models, neglecting parameter changes in the conditional volatility process results in biased estimation. The estimated sum of the autoregressive parameters of the conditional volatility converges to one. In Chapter 2, I analyze the effect of changes in the parameters of conditional...

We investigate jump memory using an extensive database of short-term S&P 500 index options. Jump memory refers to the attenuation of the implied jump intensity and magnitude parameters following a crash event. We use a genetic algorithm to obtain a time series of implied parameter estimates and...